Digital signal processing is evolving as the preferred implementation in many signal processing applications. The advent of improved, higher speed and lower cost digital signal processors (DSPs) and other digital circuit elements coupled with increased flexibility and accuracy of digital circuits is driving a move to converting a number of signal processing applications from the analog forum to the digital forum. Digital signal processing, while offering the above mentioned advantages and other advantages, does not come without some drawbacks. For example, some applications, particularly in the field of radio frequency (RF) communications, are inherently analog. Signal processing for RF applications often require converting an analog signal, for example an RF or intermediate frequency (IF) signal, to a digital signal and likewise converting digital signals to analog signals. An example of such an application is in wideband digital transceivers such as shown and described in commonly assigned U.S. patent application Ser. No. 08/366,283, the disclosure of which is hereby expressly incorporated herein by reference.
In many digital processing applications, including those accomplished in a wideband digital transceiver, the precision of a signal must be converted from a high level of precision to a lower level of precision. For example, a signal represented as 32 bits of information may have to be reduced to a signal represented as 16 bits of information. This is due to the limited capabilities of certain digital processing elements such as, for example, digital-to-analog converters (DACs). In making such a conversion, however, there is a loss of information. One will appreciate in the above example that 32 bits can represent more information than 16 bits at a given data rate. The result of this loss of information is quantization noise.
Referring to FIG. 1, a typical example is shown to illustrate the effects of quantization noise. In the application illustrated, a 16 bit digital signal X of given frequency is to be converted to an analog signal by DAC 10. However, DAC 10 is only a 12 bit device. Therefore, the signal X must be first converted to a 12 bit signal. A typical approach is to use a hard quantizer 12 which truncates the least significant bits (LSBs), in this case the 4 LSBs, of signal X to create a 12 bit signal Y. The noise relative to the carrier signal in decibels (dBc) of this application is given as: EQU noise (dBc)=20 log 2.sup.-n
where n is the number of bits of the DAC. Thus, the noise level is (-72) dBc for the 12 bit DAC and would be, for example, (-78) dBc for a 13 bit DAC, etc. Often the noise is distributed over the entire Nyquist bandwidth and the noise power per Hertz is negligible. However, frequently the noise appears at discreet frequencies, like second and third harmonics of the signal, which pose significant problems.
To overcome the problem of noise dwelling at particular frequencies, it has been proposed to introduce psuedorandom noise to the signal, often referred to as dithering. A number of dithering techniques are taught in U.S. Pat. Nos. 4,901,265, 4,951,237, 5,073,869, 5,228,054 and 5,291,428. A major disadvantage of dithering is the requirement of having to provide pseudorandom noise generator circuitry which is often complex making the application implementation intensive and costly.
Therefore, a need exists for a method and apparatus for reducing quantization noise without significantly increasing the cost and complexity of the digital signal processing circuit.